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Integrated Next-Generation Sequencing and Avatar Mouse Models for Personalized Cancer Treatment

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Integrated Next-Generation Sequencing and Avatar Mouse Models for Personalized Cancer Treatment Published OnlineFirst March 14, 2014; DOI: 10.1158/1078-0432.CCR-13-3047 Clinical Cancer Predictive Biomarkers and Personalized Medicine Research Integrated Next-Generation Sequencing and Avatar Mouse Models for Personalized Cancer Treatment Elena Garralda1, Keren Paz4, Pedro P. Lopez-Casas 1,Sian^ Jones5, Amanda Katz4, Lisa M. Kann5, Fernando Lopez-Rios 2, Francesca Sarno3,Fatima Al-Shahrour1, David Vasquez4, Elizabeth Bruckheimer4, Samuel V. Angiuoli5, Antonio Calles1, Luis A. Diaz6, Victor E. Velculescu6, Alfonso Valencia1, David Sidransky4, and Manuel Hidalgo1 Abstract Background: Current technology permits an unbiased massive analysis of somatic genetic alterations from tumor DNA as well as the generation of individualized mouse xenografts (Avatar models). This work aimed to evaluate our experience integrating these two strategies to personalize the treatment of patients with cancer. Methods: We performed whole-exome sequencing analysis of 25 patients with advanced solid tumors to identify putatively actionable tumor-specific genomic alterations. Avatar models were used as an in vivo platform to test proposed treatment strategies. Results: Successful exome sequencing analyses have been obtained for 23 patients. Tumor-specific mutations and copy-number variations were identified. All samples profiled contained relevant genomic alterations. Tumor was implanted to create an Avatar model from 14 patients and 10 succeeded. Occasionally, actionable alterations such as mutations in NF1, PI3KA, and DDR2 failed to provide any benefit when a targeted drug was tested in the Avatar and, accordingly, treatment of the patients with these drugs was not effective. To date, 13 patients have received a personalized treatment and 6 achieved durable partial remissions. Prior testing of candidate treatments in Avatar models correlated with clinical response and helped to select empirical treatments in some patients with no actionable mutations. Conclusion: The use of full genomic analysis for cancer care is encouraging but presents important challenges that will need to be solved for broad clinical application. Avatar models are a promising investigational platform for therapeutic decision making. While limitations still exist, this strategy should be further tested. Clin Cancer Res; 20(9); 2476–84. Ó2014 AACR. Introduction the characterization of the cancer genome in a time frame Cancer is considered a disease caused and driven by the that is compatible with treatment decisions, offering the accumulation of genetic aberrations (1). Virtually every opportunity to potentially increase the therapeutic efficacy cancer has its unique set of molecular changes, and the by targeting the genomic aberrations driving tumor behav- knowledge of such alterations in the clinical arena could ior (4–6). ultimately facilitate an individualized approach to cancer There are, however, still significant challenges to integrate treatment (2, 3). Recent advances in timeliness and cost of genomic testing into cancer treatment decision-making as next-generation sequencing (NGS) technologies allow for the interpretation of the genomic information is still defy- ing. On the one end, for most cancers there are a large number of mutations considered to be relevant (7, 8). While Authors' Affiliations: 1Spanish National Cancer Research Centre (CNIO), many of those are not drug targets, it is common to find Madrid, Spain; 2Champions Oncology, Baltimore, Maryland; 3Personal several potential treatment opportunities for each given Genome Diagnostics, Inc., Baltimore, Maryland; 4Laboratorio Dianas Ter- apéuticas, Hospital Universitario Madrid-Sanchinarro, Madrid, Spain; patient. How to prioritize these potential treatments is an 5Centro Integral Oncológico Clara Campal, Hospital Universitario unresolved issue (9). At present, the ability to generate Madrid-Sanchinarro, Madrid, Spain; 6Ludwig Center for Cancer Genetics genomic data supersedes the capacity to draw inferences and Therapeutics, Johns Hopkins Kimmel Cancer Center, Baltimore, Maryland from prior experiences and make informed treatment recommendations that can benefit the profiled individual Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/). patient. Novel tools to integrate genomic information with traditional clinical and pathologic data in an iterative man- Corresponding Author: Manuel Hidalgo, Centro Nacional de Investiga- ciones Oncologicas (CNIO; Spanish National Cancer Research Centre), ner are still needed (10). Here, we present our experience Melchor Fernandez Almagro n 3, E-28029 Madrid, Spain. Phone: 349- using a combined approach of exome sequencing and 1732-8000, ext. 2920; Fax: 349-1536-0432; E-mail: [email protected] personalized xenografting to define patient therapy. A key doi: 10.1158/1078-0432.CCR-13-3047 component of our approach is the development of patient- Ó2014 American Association for Cancer Research. derived xenografts, so-called Avatar mouse models, that 2476 Clin Cancer Res; 20(9) May 1, 2014 Downloaded from clincancerres.aacrjournals.org on September 24, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst March 14, 2014; DOI: 10.1158/1078-0432.CCR-13-3047 Personalized Cancer Treatment using Genomics and Avatar Models tailored by the integration of exome sequencing and Avatar Translational Relevance mouse models during the past 4 years. It represents a proof- Despite the clear potential of tailoring cancer treat- of-concept case report as it demonstrates the feasibility of ment using genomics data and the appearance of exciting combining both technologies in the clinical setting and technological advances, a plethora of challenges remain guide individual patient treatment. The protocol was Insti- to be resolved before wide-spread implementation of tutional Review Board approved and all patients signed personalized therapy. The masses of data generated by informed consent. high-throughput technologies are challenging to man- age, visualize, and convert to the knowledge required to Overview of personalized treatment approach improve patient outcomes. Personalized xenografts Patients had an exome characterization of tumor and developed in mice from patients’ tumor tissues could normal tissue and bioinformatic analysis to determine aid in the process of interpreting genomic analyses, the most biologically relevant somatic mutations. Simul- identifying actionable leads, and relating these to the taneously, we attempted to generate an Avatar mouse drug space. This work describes one of the first experi- model from the same patient. Using genomic analysis, ences to apply exome sequencing and patient-derived we integrated this information to help manually select a xenografts, so-called Avatar mouse models, to person- group of 5 to 10 treatments, which were then bench tested alizing cancer treatment in the clinic in real time. This in the Avatar mouse model to select the most effective approach is of clear interest as a means to better define treatment candidate for the patient. Figure 1 shows a optimal therapy for patients with advanced cancers. study schema. Patient eligibility All patients were adults with noncurable advanced cancer permits bench testing of treatment strategies derived from with an Eastern Cooperative Oncology Group (ECOG) the genomic analysis (11, 12). performance status 0–1 and adequate bone marrow, liver, and renal function to receive chemotherapy. Either archival Materials and Methods tumor tissue (preferentially frozen), xenograft tissue from This is a retrospective analysis of the patients that have the patient’s tumor, or tumor lesions suitable for a tumor received in our centers a personalized treatment approach biopsy were used. Figure 1. Study design schema. www.aacrjournals.org Clin Cancer Res; 20(9) May 1, 2014 2477 Downloaded from clincancerres.aacrjournals.org on September 24, 2021. © 2014 American Association for Cancer Research. Published OnlineFirst March 14, 2014; DOI: 10.1158/1078-0432.CCR-13-3047 Garralda et al. Genomic and bioinformatics analysis specimen was in an exponential growth phase, cohorts of After pathologic review, thin sections were obtained for mice with tumor sizes of 0.15 to 0.3 mL were randomized specialized dissection and purification of the tumor DNA to to several treatment groups. The xenograft provided a enrich for tumor purity. Tumor formalin-fixed paraffin- mechanism to test for the most effective agent if there embedded blocks were cut in 3 mm thick sections, stained were several candidate agents identified with exome with hematoxylin and eosin, and assessed by a pathologist sequencing and to formulate treatment recommenda- to confirm tumor type and mark regions predominantly tions for patients in whom the genomic analysis was not containing neoplasic cells and normal tissue. An adjusted contributory. number of consecutive unstained slides of 8 to 10 mm thickness were used for macro-dissection in each case to Patient treatments and follow-up yield approximately 250 ng of DNA. DNA samples were The patients included in the study started receiving con- enriched for coding regions in the genome using custom ventional treatment while exome sequencing and Avatar DNA capture approaches. Matching normal DNA was models were being generated and tested. Those that after- obtained from blood. Genomic DNA from tumor and wards presented with progressive disease received the per- normal samples were fragmented and used for Illumina sonalized treatment accordingly
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